@article{ferrera2017decentralized,
title = {Decentralized Safe Conflict Resolution for Multiple Robots in Dense Scenarios},
author = {Eduardo Ferrera and Jesús Capitán and Angel Castano and Pedro José Marrón},
url = {https://drive.google.com/open?id=1o6KHjl85_F-FwbRVx9uOD-DExQ_5fZ1g
https://drive.google.com/open?id=1qLg9TIBLzO5_eML-a5xRxVQ5ya6kdxvf
https://drive.google.com/open?id=1k33JrVj1jrnsTlxXQRvR-fG5zU3F2zNc},
doi = {https://doi.org/10.1016/j.robot.2017.01.008},
year = {2017},
date = {2017-01-01},
journal = {Robotics and Autonomous Systems},
volume = {91},
pages = {179--193},
publisher = {Elsevier},
abstract = {Multi-robot conflict resolution is a challenging problem, especially in dense environments where many robots must operate safely in a confined space. Centralized solutions do not scale well with the number of robots in dynamic scenarios: a centralized communication can cause bottlenecks and may not be robust enough when channels are unreliable; the complexity of algorithms grows with the number of robots, making online re-computation too expensive in many situations. In this work, we propose a decentralized approach for conflict resolution where robots show reactive and safe behaviors, avoiding collisions with both static and dynamic objects, even under unreliable communication conditions and with low resources. They detect conflicts with neighboring obstacles locally and then apply rules to surround them in a roundabout fashion, assuming that others will follow the same policy. The method is designed for unicycle robots with range-finder sensors, and it is able to cope with noisy sensors and second-order dynamic constraints, ensuring always collision-free navigation. Besides, a set of metrics and scenarios for benchmarking in multi-robot collision avoidance are proposed. We also compare our method with others from the state of the art through extensive simulations. Experiments with real robots are also presented in order to show the feasibility of the system.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}

Multi-robot conflict resolution is a challenging problem, especially in dense environments where many robots must operate safely in a confined space. Centralized solutions do not scale well with the number of robots in dynamic scenarios: a centralized communication can cause bottlenecks and may not be robust enough when channels are unreliable; the complexity of algorithms grows with the number of robots, making online re-computation too expensive in many situations. In this work, we propose a decentralized approach for conflict resolution where robots show reactive and safe behaviors, avoiding collisions with both static and dynamic objects, even under unreliable communication conditions and with low resources. They detect conflicts with neighboring obstacles locally and then apply rules to surround them in a roundabout fashion, assuming that others will follow the same policy. The method is designed for unicycle robots with range-finder sensors, and it is able to cope with noisy sensors and second-order dynamic constraints, ensuring always collision-free navigation. Besides, a set of metrics and scenarios for benchmarking in multi-robot collision avoidance are proposed. We also compare our method with others from the state of the art through extensive simulations. Experiments with real robots are also presented in order to show the feasibility of the system.

@inproceedings{Ferrera2013,
title = {Multi-robot operation system with conflict resolution},
author = {Eduardo Ferrera and Angel Castano and Jesús Capitán and Pedro José Marrón and Anibal Ollero},
url = {https://drive.google.com/open?id=1m_rZF2rj7A9K4NEYVr6qTDFPOMP0NCSR},
year = {2013},
date = {2013-11-01},
booktitle = {In ROBOT2013: First Iberian Robotics Conference.},
pages = {407-419},
publisher = {Springer, Cham.},
abstract = {Applications with large teams of robots are becoming more and more useful. If the scenario is very crowded or very dynamic, conflict resolution when using a shared workspace is a challenging problem. In this paper, an scalable, decentralized and reactive approach for collision avoidance is presented. The robots can navigate in a 2D environment avoiding each other and without high computational requirements. In addition to the conflict resolution algorithm, a multi-robot simulator is presented. The system is flexible and can be used to simulate different algorithms with realistic robots. Finally, an extension of the simulator is proposed in order to operate real robots in a multi-robot testbed. Results of the collision avoidance approach are shown with both real and simulated robots.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}

Applications with large teams of robots are becoming more and more useful. If the scenario is very crowded or very dynamic, conflict resolution when using a shared workspace is a challenging problem. In this paper, an scalable, decentralized and reactive approach for collision avoidance is presented. The robots can navigate in a 2D environment avoiding each other and without high computational requirements. In addition to the conflict resolution algorithm, a multi-robot simulator is presented. The system is flexible and can be used to simulate different algorithms with realistic robots. Finally, an extension of the simulator is proposed in order to operate real robots in a multi-robot testbed. Results of the collision avoidance approach are shown with both real and simulated robots.

@inproceedings{ferrera_icar13,
title = {Decentralized Collision Avoidance for Large Teams of Robots},
author = {Eduardo Ferrera and Angel Castano and Jesús Capitán and Anibal Ollero and Pedro José Marrón},
url = {https://drive.google.com/open?id=1pZBRNMPjYAthLdIEujt44EC7tle7lJDb
https://drive.google.com/open?id=1sUdyI4mgmwgqcZ3wvTJuEoDnD3lgKGLW},
year = {2013},
date = {2013-11-01},
booktitle = {In Advanced Robotics (ICAR), 2013 16th International Conference},
pages = {1-6},
organization = {IEEE},
abstract = {Collision avoidance for large teams of robots in crowded environments is a challenging problem. If the environment is dynamic and the number of robots can vary during operation, centralized approaches are not suitable, since they cannot be recomputed online. This paper proposes a decentralized algorithm which allows the robots to navigate reactively to their goals. The algorithm does not require a high computational load and scales with the number of robots. The paper focuses on robots with differential drive, and in that case, the space used for each robot when avoiding collisions is optimized, so crowded environments can be tackled. In addition, realistic controllers are proposed to regulate the speed of robots. Simulations with different configurations are shown, including a complex experiment with 100 robots trying to go through the same point.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}

Collision avoidance for large teams of robots in crowded environments is a challenging problem. If the environment is dynamic and the number of robots can vary during operation, centralized approaches are not suitable, since they cannot be recomputed online. This paper proposes a decentralized algorithm which allows the robots to navigate reactively to their goals. The algorithm does not require a high computational load and scales with the number of robots. The paper focuses on robots with differential drive, and in that case, the space used for each robot when avoiding collisions is optimized, so crowded environments can be tackled. In addition, realistic controllers are proposed to regulate the speed of robots. Simulations with different configurations are shown, including a complex experiment with 100 robots trying to go through the same point.

@inproceedings{Smeets2017TestbedExperience,
title = {Replacing Free-Ranging Robots with Alternative Mobile Nodes},
author = {Hugues Smeets and Matteo Ceriotti and Eduardo Ferrera and Pedro José Marrón},
url = {https://drive.google.com/open?id=14A9DxuwB0_VBLLp0PrRn7ADvMc3tB7JR},
year = {2017},
date = {2017-08-01},
booktitle = {26th International Conference on Computer Communications and Networks (ICCCN)},
abstract = { wide range of mobile devices, e.g., wireless sensor nodes, RFID tags and smartphones, gradually coalesces into the Internet of Things (IoT). Debugging and optimizing such systems is challenging and necessary to realize the foreseen vision. In this paper, we describe our endeavor to build and adapt a testbed enabling the analysis of different scenarios involving mobile elements. Instead of creating a versatile but expansive testbed based on free-ranging robots, we developed a set of specialized components based on model trains. Our
goal was to save costs while providing repeatable and accurate experiments where the movement of the tested devices is not provided by battery powered platforms. The contribution of this paper is to describe the iterative design and realization process for each testbed component and to quantify the trade-offs between different approaches. We discuss how our solutions evolved due to the constraints of the real experiments that were carried out on the various instances of the testbed, with a particular focus on the experience we acquired in the process and the lessons we have learned along the way},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}

wide range of mobile devices, e.g., wireless sensor nodes, RFID tags and smartphones, gradually coalesces into the Internet of Things (IoT). Debugging and optimizing such systems is challenging and necessary to realize the foreseen vision. In this paper, we describe our endeavor to build and adapt a testbed enabling the analysis of different scenarios involving mobile elements. Instead of creating a versatile but expansive testbed based on free-ranging robots, we developed a set of specialized components based on model trains. Our
goal was to save costs while providing repeatable and accurate experiments where the movement of the tested devices is not provided by battery powered platforms. The contribution of this paper is to describe the iterative design and realization process for each testbed component and to quantify the trade-offs between different approaches. We discuss how our solutions evolved due to the constraints of the real experiments that were carried out on the various instances of the testbed, with a particular focus on the experience we acquired in the process and the lessons we have learned along the way

@inproceedings{ferrera2017fast,
title = {From Fast to Accurate Wireless Map Reconstruction for Human Positioning Systems},
author = {Eduardo Ferrera and Jesús Capitán and Pedro José Marrón},
url = {https://drive.google.com/open?id=1xG5h2suhG5vITXTg9x_QjKodbPA8KfJ5},
year = {2017},
date = {2017-10-12},
booktitle = {Iberian Robotics conference},
pages = {299--310},
organization = {Springer},
abstract = {Indoor localization systems for humans are becoming commonplace for context-aware applications. In many public areas such as shopping malls or airports, existing wireless infrastructures can be used for localization, often through approaches based on fingerprinting. Although those systems do not require additional installation, a previous calibration phase is needed. This calibration task becomes tedious and time consuming for large scenarios, since the wireless signal must be measured in many different locations. This paper proposes an algorithm to perform this wireless map calibration autonomously by means of a robot. Instead of sampling thoroughly the full scenario from the beginning, our algorithm fosters a more sensible behavior when the calibration time may be limited: first, the robot tries to explore all areas to gain an overall view of the map; and then, it improves the accuracy by sampling more deeply each sector if there is remaining time. For this purpose, full coverage of individual rooms is ranked lower if others are still unexplored. Moreover, we propose some metrics to evaluate this kind of behavior and evaluate our exploration algorithm against a traditional coverage system in two different simulated scenarios.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}

Indoor localization systems for humans are becoming commonplace for context-aware applications. In many public areas such as shopping malls or airports, existing wireless infrastructures can be used for localization, often through approaches based on fingerprinting. Although those systems do not require additional installation, a previous calibration phase is needed. This calibration task becomes tedious and time consuming for large scenarios, since the wireless signal must be measured in many different locations. This paper proposes an algorithm to perform this wireless map calibration autonomously by means of a robot. Instead of sampling thoroughly the full scenario from the beginning, our algorithm fosters a more sensible behavior when the calibration time may be limited: first, the robot tries to explore all areas to gain an overall view of the map; and then, it improves the accuracy by sampling more deeply each sector if there is remaining time. For this purpose, full coverage of individual rooms is ranked lower if others are still unexplored. Moreover, we propose some metrics to evaluate this kind of behavior and evaluate our exploration algorithm against a traditional coverage system in two different simulated scenarios.

@misc{mulero2017topcon,
title = {The Integration of UAS in Internet of Things for Conservation Biology},
author = {Margarita Mulero-Pázmány and José Ramiro Martinez-de Dios and Richard Figura and Chia-Yen Shih and Marc Schwarzbach and Francisco Alarcón and Andrea Kropp and Héctor Nebot and Janek Mann and Emilian Radoi and Gianluca Dini and Antidio Viguria Jiménez and Juan José Negro and Anibal Ollero and Pedro José Marrón},
year = {2017},
date = {2017-06-28},
abstract = {In recent years, Unmanned Aircraft Systems (a.k.a. UAS, drones or RPAS) have been incorporated to
environmental studies thanks to the exponential growth of the market, the decline on prices and technological
advances that make the systems easier to operate. Small UAS can be deployed almost anywhere at any
moment and equipped with different sensors that allow gathering detailed spatio-temporal information of high
value for studies in conservation biology. Heterogeneous sensor networks, also known as Internet of Things
have also started to play a major role in environmental studies because they allow recording abundant and
diverse data in large-scale scenarios that are characteristic from natural protected areas with little human
effort.
This communication presents the unprecedented possibilities that the combination of both technologies offer
for environmental monitoring and protection. In addition to traditional image gathering from drones, we also
exploited their innovative robotic capabilities for collecting samples and download data from tagged animals.
We describe some examples of UAS integration in sensor networks addressing environmentally relevant
applications such as pollution detection and wildlife monitoring that were developed and tested in natural
protected areas.},
howpublished = {UAS applications for environmental issues, UAS4ENVIRO},
keywords = {},
pubstate = {published},
tppubtype = {misc}
}

In recent years, Unmanned Aircraft Systems (a.k.a. UAS, drones or RPAS) have been incorporated to
environmental studies thanks to the exponential growth of the market, the decline on prices and technological
advances that make the systems easier to operate. Small UAS can be deployed almost anywhere at any
moment and equipped with different sensors that allow gathering detailed spatio-temporal information of high
value for studies in conservation biology. Heterogeneous sensor networks, also known as Internet of Things
have also started to play a major role in environmental studies because they allow recording abundant and
diverse data in large-scale scenarios that are characteristic from natural protected areas with little human
effort.
This communication presents the unprecedented possibilities that the combination of both technologies offer
for environmental monitoring and protection. In addition to traditional image gathering from drones, we also
exploited their innovative robotic capabilities for collecting samples and download data from tagged animals.
We describe some examples of UAS integration in sensor networks addressing environmentally relevant
applications such as pollution detection and wildlife monitoring that were developed and tested in natural
protected areas.